This article studies weighted, generalized, least squares estimators in simple linear regression with serially correlated errors. Closed-form expressions of weighted least squares estimators and ...

In the general linear model with observations not necessarily uncorrelated or homoscedastic, Gauss-Markov regression coefficients are superior to ordinary unweighted least squares in the well known ...

which is the fourth equation above. These equations are solved iteratively, as in non-linear regression, but with the iteration now involving weighted least squares. The resulting scheme is called ...

This book discusses categorical data analysis and its implementation with the SAS System. Both nonparametric methods and model-based parametric methods are discussed. Specific topics include ...

Will Kenton is an expert on the economy and investing laws and regulations. He previously held senior editorial roles at Investopedia and Kapitall Wire and holds a MA in Economics from The New School ...

The process of using past cost information to predict future costs is called cost estimation. While many methods are used for cost estimation, the least-squares regression method of cost estimation is ...